Converting the characteristic of sounds such as voices and obtaining intended characteristic has been in practice. Conversion of the characteristic is generally carried out by changing the time domain waveform and the frequency spectrum of the sound. For example, an operation is carried out in which analog sound signals are taken in, converted to digital sound data, the waveform is changed to correspond to an intended conversion of characteristic of the digital sound data, and again converted to analog sound data. Thus, the characteristic of the speech utterance is changed as intended.
However, the conventional method of converting the characteristic described above has the following problems. The operation of changing the characteristic is carried out by first displaying the time domain waveform of the sound, frequency spectrum, and parameters of linear predictive coding (LPC), and then manipulating them. A problem is that, in order to obtain the intended characteristic by that manipulation, one has to possess expertise of the time domain waveform, frequency spectrum, and parameters of the linear predictive coding. Another problem is that one has to be well trained for the intended conversion of the characteristic in addition to the expertise.